Handling Noisy Labels for Robustly Learning from Self-Training Data for Low-Resource Sequence Labeling (N19-3)
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| Challenge: | In low-resource environments, self-training is less effective due to unreliable annotations . we combine self-teaching with noise handling to clean the self-labeled data . |
| Approach: | They propose to combine self-training with noise handling to clean unlabeled data . they propose to model clean and noisy labels separately to improve performance . |
| Outcome: | The proposed method performs better than baseline methods on Chunking and NER. |
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